景观空间动态模型研究现状和应重点解决的问题

分析了景观空间动态模型研究的现状及今后的重点发展方向。论文重点介绍了随机景观模型、邻域规则模型和景观过程模型(包括渗透模型、个体行为模型和空间生态系统模型)3类景观空间模型的发展现状、存在的主要问题以及对这些模型途径进行完善的有关工作,并从确证性分析、有效性分析与敏感性分析等3个方面阐述了模型检验技术的发展现状。最后,总结了未来景观空间动态模型发展中应重点解决的主要问题,即模型算法的优化、尺度转换、模型的复杂化与简化、模型检验与评价,通用模型的建立以及传统模型与社会经济因素衔接问题。     

Statistical methods for estimating doubling time in in vitro cell growth

Summary Doubling time has been widely used to represent the growth pattern of cells. A traditional method for finding the doubling time is to apply gray-scaled cells, where the logarithmic transformed scale is used. As an alternative statistical method, the log-linear model was recently proposed, for which actual cell numbers are used instead of the transformed gray-scaled cells. In this paper, I extend the log-linear model and propose the extended log-linear model. This model is designed for extra-Poisson variation, where the log-linear model produces the less appropriate estimate of the doubling time. Moreover, I compare statistical properties of the gray-scaled method, the log-linear model, and the extended log-linear model. For this purpose, I perform a Monte Carlo simulation study with three data-generating models: the additive error model, the multiplicative error model, and the overdispersed Poisson model. From the simulation study, I found that the gray-scaled method highly depends on the normality assumption of the gray-scaled cells; hence, this method is appropriate when the error model is multiplicative with the log-normally distributed errors. However, it is less efficient for other types of error distributions, especially when the error model is additive or the errors follow the Poisson distribution. The estimated standard error for the doubling time is not accurate in this case. The log-linear model was found to be efficient when the errors follow the Poisson distribution or nearly Poisson distribution. The efficiency of the log-linear model was decreased accordingly as the overdispersion increased, compared to the extended log-linear model. When the error model is additive or multiplicative with Gamma-distributed errors, the log-linear model is more efficient than the gray-scaled method. The extended log-linear model performs well overall for all three data-generating models. The loss of efficiency of the extended log-linear model is observed only when the error model is multiplicative with log-normally distributed errors, where the gray-scaled method is appropriate. However, the extended log-linear model is more efficient than the log-linear model in this case.     

气孔导度模型在北方农牧交错带的适用性评价——以马铃薯和油葵为例

基于北方农牧交错带主要作物马铃薯和油葵的叶片气孔导度、净光合速率和气象因子的平行观测数据,对常用气孔导度模型(Jarvis模型、Ball-Berry模型、Leuning模型和Medlyn模型)进行了适用性评价.结果表明:马铃薯的气孔导度与净光合速率呈现较强的线性关系,而油葵气孔导度与净光合速率的线性关系较弱.对于马铃薯气孔导度,Ball-Berry模型模拟效果最佳,Leuning模型和Medlyn模型次之,Jarvis模型模拟效果最差;各模型的模拟值与观测值的均方根误差(RMSE)分别为0.0331、0.0371、0.0456和0.0794 mol·m^-2·s^-1,归一化均方根误差(NRMSE)分别为26.8%、30.0%、36.9%和64.3%,拟合度(R²)分别为0.96、0.61、0.91和0.88.对于油葵的气孔导度,Jarvis模型模拟效果略好于Ball-Berry模型、Medlyn模型和Leuning模型,其RMSE分别为0.2221、0.2534、0.2547和0.2758 mol·m^-2·s^-1,NRMSE分别为40.3%、46.0%、46.2%和50.1%,R²分别为0.38、0.22、0.23和0.20.气象因子对气孔导度作用的通径分析表明,北方农牧交错带马铃薯和油葵气孔导度日变化主要受饱和水汽压差影响.模型评价结果表明用于油葵的气孔导度模型需要进一步改进.     

Reliability Analysis of the Groundwater Conceptual Model

The hydrologic model is the foundation of water resource management and planning. Conceptual model is the essential component of groundwater model. Due to limited understanding of natural hydrogeological conditions, the conceptual model is always constructed incompletely. Therefore, the uncertainty in the model's output is evitable when natural groundwater field is simulated by a single groundwater model. A synthetic groundwater model is built and regarded as the true model, and three alternative conceptual models are constructed by considering incomplete hydrogeological conditions. The outputs (groundwater budget terms from boundary conditions) of these groundwater models are analyzed statistically. The results show that when the conceptual model is closer to the true hydrogeological conditions, the distributions of outputs of the groundwater model are more concentrated on the true outputs. Therefore, the more reliable the structure of the conceptual model is, the more reliable the output of the groundwater model is. Moreover, the uncertainty caused by the conceptual model cannot be compensated by parameter uncertainty.     

大兴安岭塔河地区林火发生的优势预测模型选择

选取在经济学和社会科学领域广泛应用的零膨胀模型(zero-inflated models)和栅栏模型(Hurdle models)对大兴安岭地区林火发生进行模拟,应用赤池准则(AIC)、似然比检验(LR)和模型残差平方和(SSR)对两类共4个回归模型——零膨胀泊松模型(ZIP)、零膨胀负二项模型(ZINB)、栅栏泊松模型(PH)、栅栏负二项模型(NBH)进行拟合分析,最终选取适合此林火发生特性的预测模型.模型的AIC和SSR值表明,ZINB模型对当地林火数据的拟合度最高.运用LR检验对嵌套模型(ZINB与ZIP,NBH与PH)进行检验,结果显示: ZINB和NBH均优于各自的嵌入模型,说明负二项(NB)模型对数据结构中的过度离散现象可以很好地模拟和解释.根据研究区林火实际发生规律和两类不同模型的应用假设条件判断,零膨胀模型更适合塔河地区的林火特性.     

熟鸡肉中金黄色葡萄球菌生长预测模型的建立

【目的】研究不同浓度和不同温度条件下金黄色葡萄球菌接种在熟鸡肉中的生长情况,比较3种常见预测模型拟合的准确性,选择最适合的预测模型建立一级和二级模型,为进一步探讨建立三级模型提供数据基础。【方法】测定浓度为102、103和104 CFU/g的金黄色葡萄球菌接种在15-36°C熟鸡肉中的生长数据,使用Matlab软件分别建立修正的Gompertz、Logistic和Baranyi模型,通过比较残差和拟合度(RSS、AIC、RSE)选择最优模型,并且拟合出生长参数(迟滞期、最大比生长速率和最大细胞密度),在此基础上通过响应面方程建立二级模型。最后对模型的可靠性进行了内部和外部实验验证。【结果】36°C和29°C条件下,修正的Gompertz模型最适合;22°C和15°C条件下,最适合模型按接种浓度依次为修正的Gompertz、Logistic和Baranyi模型,综合考虑,最优模型选择修正的Gompertz模型。通过计算预测标准差(%SEP)、平方根误差(RMSE)、准确性因子(Af)和偏差因子(Bf)对建立的二级模型进行数学检验,检验结果均在可接受范围内。【结论】用修正的Gompertz方程和响应面方程建立的一、二级预测模型可以为建立三级模型提供有效、精确的基础。     

用光合-蒸散耦合模型模拟冬小麦CO2通量的日变化

根据 SPAC理论建立了一个冬小麦光合和蒸散的耦合模型。冬小麦 CO2 通量包括冠层光合、呼吸和土壤呼吸。冠层光合采用了 Farquhar光合作用生化模型 ,并通过冠层阻力的参数化将光合作用与蒸腾作用耦合起来。用涡度相关方法观测了 CO2通量 ,对模型进行了验证 ,结果显示模型可以较好地模拟 CO2 通量日变化过程。对模型的敏感性分析发现日间 CO2 通量最敏感的参数是初始量子效率。其次 ,CO2 通量对光响应曲线凸度、CO2 补偿点、凋萎点和叶面积指数的变化也有着较强的敏感性 ;夜间 CO2 通量敏感的参数是最适温度下 Rubisco催化能力和暗呼吸参数     

Decompositions for 2-Ratios-Parameter Symmetry Model in Square Contingency Tables with Ordered Categoriesat

For square contingency tables with ordered categories, Agresti (1983) considered the linear diagonals-parameter symmetry model. An extended model including that model is proposed which has only one more parameter than that model. The model also includes the conditional symmetry model considered by McCullagh (1978). Decompositions for the proposed model and Agresti's model are given.     

Butler-Volmer-Monod model for describing bio-anode polarization curves

A kinetic model of the bio-anode was developed based on a simple representation of the underlying biochemical conversions as described by enzyme kinetics, and electron transfer reactions as described by the Butler-Volmer electron transfer kinetics. This Butler-Volmer-Monod model was well able to describe the measured bio-anode polarization curves. The Butler-Volmer-Monod model was compared to the Nernst-Monod model described the experimental data significantly better. The Butler-Volmer-Monod model has the Nernst-Monod model as its full electrochemically reversible limit. Contrary to the Nernst-Monod model, the Butler-Volmer-Monod model predicts zero current at equilibrium potential. Besides, the Butler-Volmer-Monod model predicts that the apparent Monod constant is dependent on anode potential, which was supported by experimental results.     

用光合-蒸散耦合模型模拟冬小麦CO2通量的日变化

根据SPAC理论建立了一个冬小麦光合和蒸散的耦合模型.冬小麦CO2通量包括冠层光合、呼吸和土壤呼吸.冠层光合采用了Farquhar光合作用生化模型,并通过冠层阻力的参数化将光合作用与蒸腾作用耦合起来.用涡度相关方法观测了CO2通量,对模型进行了验证,结果显示模型可以较好地模拟CO2通量日变化过程.对模型的敏感性分析发现日间CO2通量最敏感的参数是初始量子效率.其次,CO2通量对光响应曲线凸度、CO2补偿点、凋萎点和叶面积指数的变化也有着较强的敏感性;夜间CO2通量敏感的参数是最适温度下Rubisco催化能力和暗呼吸参数.     

Analysis of several biomechanical models for the simulation of lamb liver behaviour using similarity coefficients from medical image

In this study, six biomechanical models for simulating lamb liver behaviour are presented. They are validated using similarity coefficients from Medical Image on reconstructed volumes from computerised tomography images. In particular, the Jaccard and Hausdorff coefficients are used. Loads of 20 and 40 g are applied to the livers and their deformation is simulated by means of the finite element method. The models used are a linear elastic model, a neo-Hookean model, a Mooney–Rivlin model, an Ogden model, a linear viscoelastic model and a viscohyperelastic model. The model that provided a behaviour that is closest to reality was the viscohyperelastic model, where the hyperelastic part was modelled with an Ogden model.     

A comparison of the peri-implant bone stress generated by the preload with screw tightening between ‘bonded’ and ‘contact’ model

A number of finite element analyses (FEAs) for the dental implant were performed without regard for preload and with all interfaces ‘fixed-bonded’. The purpose of this study was comparing the stress distributions between the conventional FEA model with all contacting interfaces ‘fixed-bonded’ (bonded model) and the model with the interfaces of the components in ‘contact’ with friction simulated as a preloaded implant (contact model). We further verified the accuracy of the result of the FEA using model experiment. In the contact model, the stress was more widely distributed than in the bonded model. From the model study, the preload induced by screw tightening generated strain at the peri-implant bone, even before the application of external force. As a result, the bonded model could not reproduce the mechanical phenomena, whereas the contact model is considered to be appropriate for analysing mechanical problems.     

Escherichia coil growth dynamics: A three-pool biochemically based description

A three-pool growth model of an individual Escherichia coli cell is described herein. The model is based on a previously developed chemically structured complex single cell growth model. The reduction in model complexity and the identification of the essential modes of motion, over the time scale of growth, is achieved by temporal decomposition and analysis of hierarchy in relaxation times. The three-pool model faithfully simulates the changes in cell size, cell shape, cell macromolecular composition, DNA initiation and termination periods, and the dependence of cell growth under abiotic glucose limitation. The predictions made by the reduced model compare favorably with both the experimental data and those of the full single cell model (SCM) without any parameter adjustments. The three-pool model has very few significant parameters and has the potential to find immediate practical use in bioreactor design and process control strategies. The model development illustrates the use of modal analysis to yield reduced physiologically realistic dynamic model of complex microbial system such as E. coll.     

Mathematical modeling of thermal physiological responses of clothed infants

The objective of this study is to develop a mathematical model for simulating the thermal physiological responses of clothed infants. By modifying and integrating Gagge's two-node model and Stolwijk's multi-node model, and coupled with the model of dynamic couple heat and moisture transfer in functional clothing, a new seven-node thermoregulation model for closed infants was developed. A series of preliminary numerical test were carried out for naked and clothed infant. The prediction of the new model was compared with the published data, the comparison results demonstrate that the model has good potential predictability.     

河北省年均降水量插值方法比较

以河北省及临近区域120个气象观测站点1971～2000年均降水量数据为基础,选择其中的40个作为检验站点,其余站点分别取80、40、20个作为插值站点,采用局部插值、整体插值、多元线性回归、综合模拟等多种插值模型讨论了降水空间插值问题,主要结论如下:插值站点数、模型类型、模型参数都会影响插值精度.局部插值模型相对误差最小值出现在Spline、IDW模型中,其次为Kridging模型,而整体模型Trend、多元线性回归模型误差均较大,但综合了局部插值模型和统计模型的综合模型一定程度上能改善插值精度及误差分布.河北省80和40个站点的最优插值模型为综合模型,20个站点的最优插值模型为IDW2.     

森林生物量估算中模型不确定性分析

单木生物量估算是区域森林生物量估算的基础。量化单木生物量模型中各种不确定性来源,分析各不确定性来源对森林生物量估算的影响,可为提高森林生物量估算精度提供理论依据。基于52株杉木地上部分生物量实测数据,建立杉木单木地上部分生物量一元与二元模型。在两种模型形式下,根据临安市2009年森林资源连续清查数据中杉木实测数据,分析单木生物量模型中所包含的2种不确定性,即模型参数不确定性和模型残差变异引起的不确定性。最后利用误差传播定律计算单木生物量模型总不确定性。结果表明,基于一元生物量模型的临安市杉木生物量估计均值为6.94 Mg/hm~2,由一元模型残差变异引起的生物量不确定性约为11.1%,模型参数误差引起的生物量不确定性约为14.4%,一元生物量模型估算合成不确定性为18.18%。基于二元生物量模型的临安市杉木生物量估计均值为7.71 Mg/hm~2,模型残差变异引起的不确定性约为7.0%,模型参数误差引起的不确定性约为8.53%,二元生物量模型估算合成不确定性为11.03%。研究表明模型参数不确定性随建模样本的增加逐渐降低,当建模样本由30增加到40再增加到52时,一元生物量模型模型参数不确定性分别为20.26%、16.19%、14.4%,二元生物量模型分别为13.09%、9.4%、8.53%。此外,建模样本的增加对残差变异不确定性也有一定影响,当建模样本由30增加到42再增加到48时,一元模型残差变异不确定性分别为15.2%,12.3%和11.7%;二元模型残差变异不确定性分别为13.3%,9.4%和8.3%。在2种不确定性来源中模型参数不确定性对估计结果影响最大,其次为模型残差变异。由于模型残差变异、参数不确定性与建模样本有关,因此可以通过增加建模样本来减小模型参数不确定性。二元生物量模型总的不确定性要低于一元生物量模型。     

A modified mathematical model of the anatomy of the cardiac left ventricle

A modification of the mathematical model of the shape and fiber direction field of the left cardiac ventricle is presented. The model was developed based on the idea of nested spiral surfaces. The ventricle is composed of surfaces that model myocardial layers. Each layer is filled with curves corresponding to myocardial fibers. The tangents to these curves form the myofiber direction field. A modified spherical coordinate system is linked with the model left ventricle, where the ventricular boundaries are coordinate surfaces. The model is based on echocardiographic, computed-tomography, or magnetic-resonance-imaging data. For this purpose, four-chamber and two-chamber echocardiography views or sections along the long axis of the left ventricle from these tomographic data in several positions are approximated with a model profile. To construct a 3D model, we then interpolate model parameters by periodic cubic splines and the vector field of the tangents to the model fibers is calculated. For verification of the model, we used diffusion-tensor magneticresonance-imaging data of the human heart.     

New modified Square Root and Schoolfield models for predicting bacterial growth rate as a function of temperature

Summary A new modified Square Root model and two new modified Schoolfield models were evaluated for their ability to predict the growth rate ofYersinia enterocolitica as a function of temperature. The new Square Root model fits the data better than both the original Square Root model and the Zwietering Square Root model. Both new Schoolfield models, a six-and a four-parameter equation, fit the data better than the original Schoolfield model. The new four-parameter Schoolfield model was developed by removing the term describing low temperature inactivation from the new six-parameter Schoolfield model. Inclusion of the two extra parameters in the new six-parameter Schoolfield model (F=318) did not significantly improve the fit compared to the new fourparameter Schoolfield model (F=488).     

The influence of model parameters on model validation

The study examined the sensitivity of two musculoskeletal models to the parameters describing each model. Two different models were examined: a phenomenological model of human jumping with parameters based on live subject data, and the second a model of the First Dorsal Interosseous with parameters based on cadaveric measurements. Both models were sensitive to the model parameters, with the use of mean group data not producing model outputs reflective of either the performance of any group member or the mean group performance. These results highlight the value of subject specific model parameters, and the problems associated with model validation.     

Coexistence of multiple pathogen strains in stochastic epidemic models with density-dependent mortality

Stochastic differential equations that model an SIS epidemic with multiple pathogen strains are derived from a system of ordinary differential equations. The stochastic model assumes there is demographic variability. The dynamics of the deterministic model are summarized. Then the dynamics of the stochastic model are compared to the deterministic model. In the deterministic model, there can be either disease extinction, competitive exclusion, where only one strain persists, or coexistence, where more than one strain persists. In the stochastic model, all strains are eventually eliminated because the disease-free state is an absorbing state. However, if the population size and the initial number of infected individuals are sufficiently large, it may take a long time until all strains are eliminated. Numerical simulations of the stochastic model show that coexistence cases predicted by the deterministic model are an unlikely occurrence in the stochastic model even for short time periods. In the stochastic model, either disease extinction or competitive exclusion occur. The initial number of infected individuals, the basic reproduction numbers, and other epidemiological parameters are important determinants of the dominant strain in the stochastic epidemic model.